In bottom-up, label-free discovery proteomics, biological samples are acquired in a data-dependent (DDA) or data-independent (DIA) manner, with peptide signals recorded in an intact (MS1) and fragmented (MS2) form. While DDA has only the MS1 space for quantification, DIA contains both MS1 and MS2 at high quantitative quality. DIA profiles of complex biological matrices such as tissues or cells can contain quantitative interferences, and the interferences at the MS1 and the MS2 signals are often independent. When comparing biological conditions, the interferences can compromise the detection of differential peptide or protein abundance and lead to false positive or false negative conclusions.

We hypothesized that the combined use of MS1 and MS2 quantitative signals could improve our ability to detect differentially abundant proteins. Therefore, we developed a statistical procedure incorporating both MS1 and MS2 quantitative information of DIA. We benchmarked the performance of the MS1-MS2-combined method to the individual use of MS1 or MS2 in DIA using four previously published controlled mixtures, as well as in two previously unpublished controlled mixtures. In the majority of the comparisons, the combined method outperformed the individual use of MS1 or MS2. This was particularly true for comparisons with low fold changes, few replicates, and situations where MS1 and MS2 were of similar quality. When applied to a previously unpublished investigation of lung cancer, the MS1-MS2-combined method increased the coverage of known activated pathways.

Since recent technological developments continue to increase the quality of MS1 signals (e.g. using the BoxCar scan mode for Orbitrap instruments), the combination of the MS1 and MS2 information has a high potential for future statistical analysis of DIA data.

Top-down proteomics studies intact proteoform mixtures and offers important advantages over more common bottom-up proteomics technologies, as it avoids the protein inference problem. However, achieving complete molecular characterization of investigated proteoforms using existing technologies remains a fundamental challenge for top-down proteomics. Here, we benchmark the performance of ultraviolet photodissociation (UVPD) using 213 nm photons generated by a solid-state laser applied to the study of intact proteoforms from three organisms. Notably, the described UVPD setup applies multiple laser pulses to induce ion dissociation, and this feature can be used to optimize the fragmentation outcome based on the molecular weight of the analyzed biomolecule. When applied to complex proteoform mixtures in high-throughput top-down proteomics, 213 nm UVPD demonstrated a high degree of complementarity with the most employed fragmentation method in proteomics studies, higher-energy collisional dissociation (HCD). UVPD at 213 nm offered higher average proteoform sequence coverage and degree of proteoform characterization (including localization of post-translational modifications) than HCD. However, previous studies have shown limitations in applying database search strategies developed for HCD fragmentation to UVPD spectra which contains up to nine fragment ion types. We therefore performed an analysis of the different UVPD product ion type frequencies. From these data, we developed an ad hoc fragment matching strategy and determined the influence of each possible ion type on search outcomes. By paring down the number of ion types considered in high-throughput UVPD searches from all types down to the four most abundant, we were ultimately able to achieve deeper proteome characterization with UVPD. Lastly, our detailed product ion analysis also revealed UVPD cleavage propensities and determined the presence of a product ion produced specifically by 213 nm photons. All together, these observations could be used to better elucidate UVPD dissociation mechanisms and improve the utility of the technique for proteomic applications.

The molecular mechanisms underlying exceptional radioresistance in pancreatic cancer remain elusive. In the present study, we established a stable radioresistant pancreatic cancer cell line MIA PaCa-2-R by exposing the parental MIA PaCa-2 cells to fractionated ionizing radiation (IR). Systematic proteomics and bioinformatics analysis of protein expression in MIA PaCa-2 and MIA PaCa-2-R cells revealed that several growth factor-/cytokine-mediated pathways, including the OSM/STAT3, PI3K/AKT, and MAPK/ERK pathways, were activated in the radioresistant cells, leading to inhibition of apoptosis and increased epithelial-mesenchymal plasticity. In addition, the radioresistant cells exhibited enhanced capabilities of DNA repair and antioxidant defense compared with the parental cells. We focused functional analysis on one of the most up-regulated proteins in the radioresistant cells, ecto-5'-nucleotidase (CD73), which is a cell surface protein that is overexpressed in different types of cancer. Ectopic overexpression of CD73 in the parental cells resulted in radioresistance and conferred resistance to IR-induced apoptosis. Knockdown of CD73 re-sensitized the radioresistant cells to IR and IR-induced apoptosis. The effect of CD73 on radioresistance and apoptosis is independent of the enzymatic activity of CD73. Further studies demonstrate that CD73 up-regulation promotes Ser-136 phosphorylation of the proapoptotic protein BAD and is required for maintaining the radioresistant cells in a mesenchymal state. Our findings suggest that expression alterations in the IR-selected pancreatic cancer cells result in hyperactivation of the growth factor/cytokine signaling that promotes epithelial-mesenchymal plasticity and enhancement of DNA repair. Our results also suggest that CD73, potentially a novel downstream factor of the enhanced growth factor/cytokine signaling, confers acquired radioresistance by inactivating proapoptotic protein BAD via phosphorylation of BAD at Ser-136 and by maintaining the radioresistant pancreatic cancer cells in a mesenchymal state.

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with very limited therapeutic options. We have recently shown that the combined inhibition of EGFR and ROCK in TNBC cells results in cell death, however, the underlying mechanisms remain unclear. To investigate this, here we applied a mass spectrometry-based proteomic approach to identify proteins altered on single and combination treatments. Our proteomic data revealed autophagy as the major molecular mechanism implicated in the cells' response to combinatorial treatment. We here show that EGFR inhibition by gefitinib treatment alone induces autophagy, a cellular recycling process that acts as a cytoprotective response for TNBC cells. However, combined inhibition of EGFR and ROCK leads to autophagy blockade and accumulation of autophagic vacuoles. Our data show impaired autophagosome clearance as a likely cause of antitumor activity. We propose that the inhibition of the autophagic flux on combinatorial treatment is attributed to the major cytoskeletal changes induced on ROCK inhibition, given the essential role the cytoskeleton plays throughout the various steps of the autophagy process.

Triple-negative breast cancer (TNBC) is characterized by poor response to therapy and low overall patient survival. Recently, Estrogen Receptor beta (ERβ) has been found to be expressed in a fraction of TNBCs where, because of its oncosuppressive actions on the genome, it represents a potential therapeutic target, provided a better understanding of its actions in these tumors becomes available. To this end, the cell lines Hs 578T, MDA-MB-468 and HCC1806, representing the claudin-low, basal-like 1 and 2 TNBC molecular subtypes respectively, were engineered to express ERβ under the control of a Tetracycline-inducible promoter and used to investigate the effects of this transcription factor on gene activity. The antiproliferative effects of ERβ in these cells were confirmed by multiple functional approaches, including transcriptome profiling and global mapping of receptor binding sites in the genome, that revealed direct negative regulation by ERβ of genes, encoding for key components of cellular pathways associated to TNBC aggressiveness representing novel therapeutic targets such as angiogenesis, invasion, metastasis and cholesterol biosynthesis. Supporting these results, interaction proteomics by immunoprecipitation coupled to nano LC-MS/MS mass spectrometry revealed ERβ association with several potential nuclear protein partners, including key components of regulatory complexes known to control chromatin remodeling, transcriptional and post-transcriptional gene regulation and RNA splicing. Among these, ERβ association with the Polycomb Repressor Complexes 1 and 2 (PRC1/2), known for their central role in gene regulation in cancer cells, was confirmed in all three TNBC subtypes investigated, suggesting its occurrence independently from the cellular context. These results demonstrate a significant impact of ERβ in TNBC genome activity mediated by its cooperation with regulatory multiprotein chromatin remodeling complexes, providing novel ground to devise new strategies for the treatment of these diseases based on ligands affecting the activity of this nuclear receptor or some of its protein partners.

Proteins that bind carbohydrate structures can serve as tools to quantify or localize specific glycans in biological specimens. Such proteins, including lectins and glycan-binding antibodies, are particularly valuable if accurate information is available about the glycans that a protein binds. Glycan arrays have been transformational for uncovering rich information about the nuances and complexities of glycan-binding specificity. A challenge, however, has been the analysis of the data. Because protein-glycan interactions are so complex, simplistic modes of analyzing the data and describing glycan-binding specificities have proven inadequate in many cases. This review surveys the methods for handling high-content data on protein-glycan interactions. We contrast the approaches that have been demonstrated and provide an overview of the resources that are available. We also give an outlook on the promising experimental technologies for generating new insights into protein-glycan interactions, as well as a perspective on the limitations that currently face the field.

Lung cancer (LC) remains the leading cause of mortality from malignant tumors worldwide. In our previous study, we surveyed both IgG and IgM-bound serological biomarkers and validated a panel of IgG-bound autoantigens for early LC diagnosis with 50% sensitivity at 90% specificity. To further improve the performance of these serological biomarkers, we surveyed HuProt arrays, comprised of 20,240 human proteins, for IgA-bound autoantigens because IgAs are a major immunoglobulin isotype in the lung. Integrating with IgG-bound autoantigens, we discovered and validated a combined biomarker panel using ELISA-format tests. Specifically, in Phase I, we obtained IgA-based autoimmune profiles of 69 early stage LC patients, 30 healthy subjects and 25 patients with lung benign lesions (LBL) on HuProt arrays and identified 28 proteins as candidate autoantigens that were significantly associated with early stage LC. In Phase II, we re-purified the autoantigens and converted them into an ELISA-format testing to profile an additional large cohort, comprised of 136 early stage LC patients, 58 healthy individuals, and 29 LBL patients. Integration of IgG autoimmune profiles allowed us to identify and validate a biomarker panel of three IgA autoantigens (i.e. BCL7A, and TRIM33 and MTERF4) and three IgG autoantigens (i.e. CTAG1A, DDX4 and MAGEC2) for diagnosis of early stage LC with 73.5% sensitivity at >85% specificity. In Phase III, the performance of this biomarker panel was confirmed with an independent cohort, comprised of 88 early stage LC patients, 18 LBL patients, and 36 healthy subjects. Finally, a blind test on 178 serum samples was conducted to confirm the performance of the biomarker panel. In summary, this study demonstrates for the first time that an integrated panel of IgA/IgG autoantigens can serve as valuable biomarkers to further improve the performance of early diagnosis of LC.

For more than two decades naturally presented, human leukocyte antigen (HLA)-restricted peptides (immunopeptidome) have been eluted and sequenced using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Since, identified disease-associated HLA ligands have been characterized and evaluated as potential active substances. Treatments based on HLA-presented peptides have shown promising results in clinical application as personalized T cell-based immunotherapy. Peptide vaccination cocktails are produced as investigational medicinal products under GMP conditions. To support clinical trials based on HLA-presented tumor-associated antigens, in this study the sensitive LC-MS/MS HLA class I antigen identification pipeline was fully validated for our technical equipment according to the current US Food and Drug Administration (FDA) and European Medicines Agency (EMA) guidelines.

The immunopeptidomes of JY cells with or without spiked-in, isotope labeled peptides, of peripheral blood mononuclear cells of healthy volunteers as well as a chronic lymphocytic leukemia and a bladder cancer sample were reliably identified using a data-dependent acquisition method. As the LC-MS/MS pipeline is used for identification purposes, the validation parameters include accuracy, precision, specificity, limit of detection and robustness.

Neoantimycins are anticancer compounds of 15-membered ring antimycin-type depsipeptides. They are biosynthesized by a hybrid multimodular protein complex of nonribosomal peptide synthetase (NRPS) and polyketide synthase (PKS), typically from the starting precursor 3-formamidosalicylate. Examining fermentation extracts of Streptomyces conglobatus, here we discovered four new neoantimycin analogs, unantimycins B–E, in which 3-formamidosalicylates are replaced by an unusual 3-hydroxybenzoate (3-HBA) moiety. Unantimycins B–E exhibited levels of anticancer activities similar to those of the chemotherapeutic drug cisplatin in human lung cancer, colorectal cancer, and melanoma cells. Notably, they mostly displayed no significant toxicity toward noncancerous cells, unlike the serious toxicities generally reported for antimycin-type natural products. Using site-directed mutagenesis and heterologous expression, we found that unantimycin productions are correlated with the activity of a chorismatase homolog, the nat-hyg5 gene, from a type I PKS gene cluster. Biochemical analysis confirmed that the catalytic activity of Nat-hyg5 generates 3-HBA from chorismate. Finally, we achieved selective production of unantimycins B and C by engineering a chassis host. On the basis of these findings, we propose that unantimycin biosynthesis is directed by the neoantimycin-producing NRPS–PKS complex and initiated with the starter unit of 3-HBA. The elucidation of the biosynthetic unantimycin pathway reported here paves the way to improve the yield of these compounds for evaluation in oncotherapeutic applications.

The cellular energy sensor AMP-activated protein kinase (AMPK) is a metabolic regulator that mediates adaptation to nutritional variations to maintain a proper energy balance in cells. We show here that suckling-weaning and fasting-refeeding transitions in rodents are associated with changes in AMPK activation and the cellular energy state in the liver. These nutritional transitions were characterized by a metabolic switch from lipid to glucose utilization, orchestrated by modifications in glucose levels and the glucagon/insulin ratio in the bloodstream. We therefore investigated the respective roles of glucose and pancreatic hormones on AMPK activation in mouse primary hepatocytes. We found that glucose starvation transiently activates AMPK, whereas changes in glucagon and insulin levels had no impact on AMPK. Challenge of hepatocytes with metformin-induced metabolic stress strengthened both AMPK activation and cellular energy depletion under limited-glucose conditions, whereas neither glucagon nor insulin altered AMPK activation. Although both insulin and glucagon induced AMPKα phosphorylation at its Ser485/491 residue, they did not affect its activity. Finally, the decrease in cellular ATP levels in response to an energy stress was additionally exacerbated under fasting conditions and by AMPK deficiency in hepatocytes, revealing metabolic inflexibility and emphasizing the importance of AMPK for maintaining hepatic energy charge. Our results suggest that nutritional changes (i.e. glucose availability), rather than the related hormonal changes (i.e. the glucagon/insulin ratio), sensitize AMPK activation to the energetic stress induced by the dietary transition during fasting. This effect is critical for preserving the cellular energy state in the liver.

Phosphoglycerate kinase 1 (PGK1) plays important roles in glycolysis, yet its forward reaction kinetics are unknown, and its role especially in regulating cancer cell glycolysis is unclear. Here, we developed an enzyme assay to measure the kinetic parameters of the PGK1-catalyzed forward reaction. The Km values for 1,3-bisphosphoglyceric acid (1,3-BPG, the forward reaction substrate) were 4.36 μm (yeast PGK1) and 6.86 μm (human PKG1). The Km values for 3-phosphoglycerate (3-PG, the reverse reaction substrate and a serine precursor) were 146 μm (yeast PGK1) and 186 μm (human PGK1). The Vmax of the forward reaction was about 3.5- and 5.8-fold higher than that of the reverse reaction for the human and yeast enzymes, respectively. Consistently, the intracellular steady-state concentrations of 3-PG were between 180 and 550 μm in cancer cells, providing a basis for glycolysis to shuttle 3-PG to the serine synthesis pathway. Using siRNA-mediated PGK1-specific knockdown in five cancer cell lines derived from different tissues, along with titration of PGK1 in a cell-free glycolysis system, we found that the perturbation of PGK1 had no effect or only marginal effects on the glucose consumption and lactate generation. The PGK1 knockdown increased the concentrations of fructose 1,6-bisphosphate, dihydroxyacetone phosphate, glyceraldehyde 3-phosphate, and 1,3-BPG in nearly equal proportions, controlled by the kinetic and thermodynamic states of glycolysis. We conclude that perturbation of PGK1 in cancer cells insignificantly affects the conversion of glucose to lactate in glycolysis.

Triple-negative breast cancer (TNBC) is characterized by its aggressive biology, early metastatic spread, and poor survival outcomes. TNBC lacks expression of the targetable receptors found in other breast cancer subtypes, mandating use of cytotoxic chemotherapy. However, resistance to chemotherapy is a significant problem, encountered in about two-thirds of TNBC patients, and new strategies are needed to mitigate resistance. In this issue of the Journal of Biological Chemistry, Geck et al. report that TNBC cells are highly sensitive to inhibition of the de novo polyamine synthesis pathway and that inhibition of this pathway sensitizes cells to TNBC-relevant chemotherapy, uncovering new opportunities for addressing chemoresistance.

Treatment of patients with triple-negative breast cancer (TNBC) is limited by a lack of effective molecular therapies targeting this disease. Recent studies have identified metabolic alterations in cancer cells that can be targeted to improve responses to standard-of-care chemotherapy regimens. Using MDA-MB-468 and SUM-159PT TNBC cells, along with LC-MS/MS and HPLC metabolomics profiling, we found here that exposure of TNBC cells to the cytotoxic chemotherapy drugs cisplatin and doxorubicin alter arginine and polyamine metabolites. This alteration was because of a reduction in the levels and activity of a rate-limiting polyamine biosynthetic enzyme, ornithine decarboxylase (ODC). Using gene silencing and inhibitor treatments, we determined that the reduction in ODC was mediated by its negative regulator antizyme, targeting ODC to the proteasome for degradation. Treatment with the ODC inhibitor difluoromethylornithine (DFMO) sensitized TNBC cells to chemotherapy, but this was not observed in receptor-positive breast cancer cells. Moreover, TNBC cell lines had greater sensitivity to single-agent DFMO, and ODC levels were elevated in TNBC patient samples. The alterations in polyamine metabolism in response to chemotherapy, as well as DFMO-induced preferential sensitization of TNBC cells to chemotherapy, reported here suggest that ODC may be a targetable metabolic vulnerability in TNBC.

It turns out that even death needs the internet.

Invitation Only Research Event

Event participants

Professor Robert Shiller, Sterling Professor of Economics, Yale University
Chair: Marianne Schneider-Petsinger, Research Fellow, US and the Americas Programme Chatham House

Invitation Only Research Event

6 November 2019 , Volume 95, Number 6

2 March 2020

4 March 2020 , Volume 96, Number 2

19 March 2020

Corporate Members Event Webinar

Che Sidanius, Global Head of Regulation & Industry Affairs, Refinitiv

Patricia Sullivan, Global Co-Head, Financial Crime Compliance, Standard Chartered

Dame Sara Thornton, Independent Anti-Slavery Commissioner, UK

Chair: Tom Keatinge, Director, Centre for Financial Crime and Security Studies, RUSI

Liam R. Brunham
Apr 1, 2020; 61:468-469
Commentary

Edward A Dennis
Apr 28, 2020; 0:jlr.T120000868v1-jlr.T120000868
Tribute

Mustafa Yalcinkaya
Apr 1, 2020; 61:492-504
Research Articles

Delphine Fontaine
Apr 7, 2020; 0:jlr.RA120000634v1-jlr.RA120000634
Research Articles

Scott Carey assembles half the Tech Advisor squad to chat about the HomePod's great audio and then all the things that make it a tabloid headline. Jim Martin lets us know if Apple ruined his oak and/or pine.

Lewis Painter chats us through Kingdom Come: Deliverance and all the wacky things you can do in its slow paced but huge world. Dom Preston then lets us know - without spoilers - just how good Black Panther is, Marvel's latest marvel (hopefully).

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This manuscript has been withdrawn by the Author.

This article has been withdrawn by the authors as part of this review overlapped with the contents of Pietrangelo A and Ridgway ND. 2018. Cellular and Molecular Life Sciences. 75; 3079-98.

Ether lipids (ELs) are lipids characterized by the presence of either an ether linkage (alkyl lipids) or a vinyl ether linkage (i.e. plasmalogens [Pls]) at the sn1 position of the glycerol backbone and they are enriched in PUFAs at the sn2 position. In this review, we highlight that ELs have various biological functions, act as a reservoir for second messengers (such as PUFAs), and have roles in many diseases. Some of the biological effects of ELs may be associated with their ability to regulate ion channels that control excitation-contraction/secretion/mobility coupling and therefore cell physiology. These channels are embedded in lipid membranes, and lipids can regulate their activities directly or indirectly as second messengers or by incorporating into membranes. Interestingly, ELs and EL-derived PUFAs have been reported to play a key role in several pathologies, including neurological disorders, cardiovascular diseases, and cancers. Investigations leading to a better understanding of their mechanisms of action in pathologies have opened a new field in cancer research. In summary, newly identified lipid regulators of ion channels, such as ELs and PUFAs, may represent valuable targets to improve disease diagnosis and advance the development of new therapeutic strategies for managing a range of diseases and conditions.

19 March 2020

29 March 2020

Colorectal cancer (CRC) arises as the consequence of progressive changes from normal epithelial cells through polyp to tumor, and thus is an useful model for studying metabolic shift. In the present study, we studied the metabolomic profiles using high analyte specific gas chromatography/mass spectrometry (GC/MS) and liquid chromatography tandem mass spectrometry (LC/MS/MS) to attain a systems-level view of the shift in metabolism in cells progressing along the path to CRC. Colonic tissues including tumor, polyps and adjacent matched normal mucosa from 26 patients with sporadic CRC from freshly isolated resections were used for this study. The metabolic profiles were obtained using GC/MS and LC/MS/MS. Our data suggest there was a distinct profile change of a wide range of metabolites from mucosa to tumor tissues. Various amino acids and lipids in the polyps and tumors were elevated, suggesting higher energy needs for increased cellular proliferation. In contrast, significant depletion of glucose and inositol in polyps revealed that glycolysis may be critical in early tumorigenesis. In addition, the accumulation of hypoxanthine and xanthine, and the decrease of uric acid concentration, suggest that the purine biosynthesis pathway could have been substituted by the salvage pathway in CRC. Further, there was a step-wise reduction of deoxycholic acid concentration from mucosa to tumors. It appears that to gain a growth advantage, cancer cells may adopt alternate metabolic pathways in tumorigenesis and this flexibility allows them to adapt and thrive in harsh environment.

Protein tyrosine kinases (PTKs) play key roles in cellular signal transduction, cell cycle regulation, cell division, and cell differentiation. Dysregulation of PTK-activated pathways, often by receptor overexpression, gene amplification, or genetic mutation, is a causal factor underlying numerous cancers. In this study, we have developed a parallel reaction monitoring (PRM)-based assay for quantitative profiling of 83 PTKs. The assay detects 308 proteotypic peptides from 54 receptor tyrosine kinases and 29 nonreceptor tyrosine kinases in a single run. Quantitative comparisons were based on the labeled reference peptide method. We implemented the assay in four cell models: 1) a comparison of proliferating versus epidermal growth factor (EGF)-stimulated A431 cells, 2) a comparison of SW480Null (mutant APC) and SW480APC (APC restored) colon tumor cell lines, and 3) a comparison of 10 colorectal cancer cell lines with different genomic abnormalities, and 4) lung cancer cell lines with either susceptibility (11-18) or acquired resistance (11-18R) to the epidermal growth factor receptor tyrosine kinase inhibitor erlotinib. We observed distinct PTK expression changes that were induced by stimuli, genomic features or drug resistance, which were consistent with previous reports. However, most of the measured expression differences were novel observations. For example, acquired resistance to erlotinib in the 11-18 cell model was associated not only with previously reported upregulation of MET, but also with upregulation of FLK2 and downregulation of LYN and PTK7. Immunoblot analyses and shotgun proteomics data were highly consistent with PRM data. Multiplexed PRM assays provide a targeted, systems-level profiling approach to evaluate cancer-related proteotypes and adaptations. Data are available through Proteome eXchange Accession PXD002706.

Ion mobility can add a dimension to LC-MS based shotgun proteomics which has the potential to boost proteome coverage, quantification accuracy and dynamic range.  Required for this is suitable software that extracts the information contained in the four-dimensional (4D) data space spanned by m/z, retention time, ion mobility and signal intensity. Here we describe the ion mobility enhanced MaxQuant software, which utilizes the added data dimension. It offers an end to end computational workflow for the identification and quantification of peptides and proteins in LC-IMS-MS/MS shotgun proteomics data. We apply it to trapped ion mobility spectrometry (TIMS) coupled to a quadrupole time-of-flight (QTOF) analyzer. A highly parallelizable 4D feature detection algorithm extracts peaks which are assembled to isotope patterns. Masses are recalibrated with a non-linear m/z, retention time, ion mobility and signal intensity dependent model, based on peptides from the sample. A new matching between runs (MBR) algorithm that utilizes collisional cross section (CCS) values of MS1 features in the matching process significantly gains specificity from the extra dimension. Prerequisite for using CCS values in MBR is a relative alignment of the ion mobility values between the runs. The missing value problem in protein quantification over many samples is greatly reduced by CCS aware MBR.MS1 level label-free quantification is also implemented which proves to be highly precise and accurate on a benchmark dataset with known ground truth. MaxQuant for LC-IMS-MS/MS is part of the basic MaxQuant release and can be downloaded from http://maxquant.org.

Quantitative proteomics by mass spectrometry is widely used in biomarker research and basic biology research for investigation of phenotype level cellular events. Despite the wide application, the methodology for statistical analysis of differentially expressed proteins has not been unified. Various methods such as t-test, linear model and mixed effect models are used to define changes in proteomics experiments. However, none of these methods consider the specific structure of MS-data. Choices between methods, often originally developed for other types of data, are based on compromises between features such as statistical power, general applicability and user friendliness. Furthermore, whether to include proteins identified with one peptide in statistical analysis of differential protein expression varies between studies. Here we present DEqMS, a robust statistical method developed specifically for differential protein expression analysis in mass spectrometry data. In all datasets investigated there is a clear dependence of variance on the number of PSMs or peptides used for protein quantification. DEqMS takes this feature into account when assessing differential protein expression. This allows for a more accurate data-dependent estimation of protein variance and inclusion of single peptide identifications without increasing false discoveries. The method was tested in several datasets including E.coli proteome spike-in data, using both label-free and TMT-labelled quantification. In comparison to previous statistical methods used in quantitative proteomics, DEqMS showed consistently better accuracy in detecting altered protein levels compared to other statistical methods in both label-free and labelled quantitative proteomics data. DEqMS is available as an R package in Bioconductor.

The onset of obesity-linked type 2 diabetes (T2D) is marked by an eventual failure in pancreatic β-cell function and mass that is no longer able to compensate for the inherent insulin resistance and increased metabolic load intrinsic to obesity. However, in a commonly used model of T2D, the db/db mouse, β-cells have an inbuilt adaptive flexibility enabling them to effectively adjust insulin production rates relative to the metabolic demand. Pancreatic β-cells from these animals have markedly reduced intracellular insulin stores, yet high rates of (pro)insulin secretion, together with a substantial increase in proinsulin biosynthesis highlighted by expanded rough endoplasmic reticulum and Golgi apparatus. However, when the metabolic overload and/or hyperglycemia is normalized, β-cells from db/db mice quickly restore their insulin stores and normalize secretory function. This demonstrates the β-cell’s adaptive flexibility and indicates that therapeutic approaches applied to encourage β-cell rest are capable of restoring endogenous β-cell function. However, mechanisms that regulate β-cell adaptive flexibility are essentially unknown. To gain deeper mechanistic insight into the molecular events underlying β-cell adaptive flexibility in db/db β-cells, we conducted a combined proteomic and post-translational modification specific proteomic (PTMomics) approach on islets from db/db mice and wild-type controls (WT) with or without prior exposure to normal glucose levels. We identified differential modifications of proteins involved in redox homeostasis, protein refolding, K48-linked deubiquitination, mRNA/protein export, focal adhesion, ERK1/2 signaling, and renin-angiotensin-aldosterone signaling, as well as sialyltransferase activity, associated with β-cell adaptive flexibility. These proteins are all related to proinsulin biosynthesis and processing, maturation of insulin secretory granules, and vesicular trafficking—core pathways involved in the adaptation of insulin production to meet metabolic demand. Collectively, this study outlines a novel and comprehensive global PTMome signaling map that highlights important molecular mechanisms related to the adaptive flexibility of β-cell function, providing improved insight into disease pathogenesis of T2D.

7 May 2020 , Volume 96, Number 3

Invitation Only Research Event

Event participants

Yang Cheng, Professor of International Relations, Assistant Dean, School of International Relations and Public Affairs, Shanghai International Studies University
Yu Jie, Senior Research Fellow, Asia-Pacific Programme, Chatham House
Marcin Kaczmarski, Lecturer in Security Studies, University of Glasgow
Natasha Kuhrt, Lecturer, Department of War Studies, King’s College London
Bobo Lo, Non-Resident Fellow, Lowy Institute
Alexey Maslov, Professor, School of Asian Studies, National Research University, Higher School of Economics, Moscow

29 March 2020

Invitation Only Research Event

Event participants

Maria Shagina, CEES Postdoctoral Fellow, Center for Eastern European Studies, University of Zurich
Chair: Richard Connolly, Associate Fellow, Russia and Eurasia Programme, Chatham House

We previously described the expression of CD36 and LPL by breast cancer (BC) cells and tissues and the growth-promoting effect of VLDL observed only in the presence of LPL. We now report a model in which LPL is bound to a heparan sulfate proteoglycan motif on the BC cell surface and acts in concert with the VLDL receptor to internalize VLDLs via receptor-mediated endocytosis. We also demonstrate that gene-expression programs for lipid synthesis versus uptake respond robustly to triglyceride-rich lipoprotein availability. The literature emphasizes de novo FA synthesis and exogenous free FA uptake using CD36 as paramount mechanisms for lipid acquisition by cancer cells. We find that the uptake of intact lipoproteins is also an important mechanism for lipid acquisition and that the relative reliance on lipid synthesis versus uptake varies among BC cell lines and in response to VLDL availability. This metabolic plasticity has important implications for the development of therapies aimed at the lipid dependence of many types of cancer, in that the inhibition of FA synthesis may elicit compensatory upregulation of lipid uptake. Moreover, the mechanism that we have elucidated provides a direct connection between dietary fat and tumor biology.­.

Loss of pancreatic β-cell mass and function as a result of sustained ER stress is a core step in the pathogenesis of diabetes mellitus type 2. The complex control of β-cells and insulin production involves hedgehog (Hh) signaling pathways as well as cholesterol-mediated effects. In fact, data from studies in humans and animal models suggest that HDL protects against the development of diabetes through inhibition of ER stress and β-cell apoptosis. We investigated the mechanism by which HDL inhibits ER stress and apoptosis induced by thapsigargin, a sarco/ER Ca²⁺-ATPase inhibitor, in β-cells of a rat insulinoma cell line, INS1e. We further explored effects on the Hh signaling receptor Smoothened (SMO) with pharmacologic agonists and inhibitors. Interference with sterol synthesis or efflux enhanced β-cell apoptosis and abrogated the anti-apoptotic activity of HDL. During ER stress, HDL facilitated the efflux of specific oxysterols, including 24-hydroxycholesterol (OHC). Supplementation of reconstituted HDL with 24-OHC enhanced and, in cells lacking ABCG1 or the 24-OHC synthesizing enzyme CYP46A1, restored the protective activity of HDL. Inhibition of SMO countered the beneficial effects of HDL and also LDL, and SMO agonists decreased β-cell apoptosis in the absence of ABCG1 or CYP46A1. The translocation of the SMO-activated transcription factor glioma-associated oncogene GLI-1 was inhibited by ER stress but restored by both HDL and 24-OHC. In conclusion, the protective effect of HDL to counter ER stress and β-cell death involves the transport, generation, and mobilization of oxysterols for activation of the Hh signaling receptor SMO

Cholesterol/sphingolipid-rich membrane domains, known as lipid rafts or membrane rafts, play a critical role in the compartmentalization of signaling pathways. Physical segregation of proteins in lipid rafts may modulate the accessibility of proteins to regulatory or effector molecules. Thus, lipid rafts serve as sorting platforms and hubs for signal transduction proteins. Cancer cells contain higher levels of intracellular cholesterol and lipid rafts than their normal non-tumorigenic counterparts. Many signal transduction processes involved in cancer development (insulin-like growth factor system and phosphatidylinositol 3-kinase-AKT) and metastasis [cluster of differentiation (CD)44] are dependent on or modulated by lipid rafts. Additional proteins playing an important role in several malignant cancers (e.g., transmembrane glycoprotein mucin 1) are also being detected in association with lipid rafts, suggesting a major role of lipid rafts in tumor progression. Conversely, lipid rafts also serve as scaffolds for the recruitment and clustering of Fas/CD95 death receptors and downstream signaling molecules leading to cell death-promoting raft platforms. The partition of death receptors and downstream signaling molecules in aggregated lipid rafts has led to the formation of the so-called cluster of apoptotic signaling molecule-enriched rafts, or CASMER, which leads to apoptosis amplification and can be pharmacologically modulated. These death-promoting rafts can be viewed as a linchpin from which apoptotic signals are launched. In this review, we discuss the involvement of lipid rafts in major signaling processes in cancer cells, including cell survival, cell death, and metastasis, and we consider the potential of lipid raft modulation as a promising target in cancer therapy.

When the problem occurs, you are unable to perform any workflow actions in a SAS solution that uses SAS Workflow Services.

A sign-on to a grid-enabled environment fails while it is trying to communicate with the client host. The following errors then appear in the SAS log: